The financial industry is among those under the most pressure to innovate. Fintech companies are cannibalizing traditional banking domains. Customers demand better, faster, and fully digital banking experiences, while banking CIOs are directing most of their IT budgets towards supporting legacy core systems written in COBOL.
However, staying too focused on support and maintenance is hardly a viable business strategy. Gartner warns that by 2030 as much as 80% of heritage financial services firms can become obsolete unless they digitize and innovate.
If you want to maximize your returns on IT investments, pursuing innovations in the wealth management space can be your best move.
Why wealth management is a strong contender for innovations
For a long time, personalized financial advisory services were reserved for a top-5% percentile of high net-worth individuals. Today, that’s no longer the case. Innovative fintech startups like Wealthfront, SoFi, and Betterment have commoditized access to financial planning services with the help of predictive analytics and machine learning algorithms. This leaves banks, still relying on human advisors, at a major disadvantage. After all, robo-advisors are more cost-efficient than traditional brokers. Accenture estimates that such algorithms can reduce the price of delivering some financial services by as much as 70%.
Moreover, personalized advisory services are the key to engaging and retaining new consumer demographics such as millennials and Gen Z. Already, 46% of consumers admit that they feel overwhelmed when it comes to financial affairs. Empowering them with the right tools can help you secure their loyalty for the next decade. That is particularly important as, by 2029, millennials will control the largest share of disposable income, making them the ideal candidates for wealth management services.
How financial institutions are taking advantage of AI
Morgan Stanley is arguably the leader in the AI advisory space. Its recently launched WealthDesk platform empowers financial employees with real-time customer insights and tools for advanced scenario analysis to propose the optimal investment strategy for the client. Post-implementation, the firm’s wealth management unit reported a pre-tax margin of 27.1% in the third quarter of 2018, up from 26.8% in the second quarter and 26.5% in 2017.
Some of the best trading platforms also leverage AI to augment and enhance the traders’ experience. For the past several years, E*Trade has been focused on migrating from legacy data centers to a more agile cloud architecture that would also free up IT staff to work on innovative products. Introducing a higher level of automation and, ultimately, AI algorithms have been a priority, too: “There are certain things humans do well and certain things they don’t. The repetitive, rote task typically is better suited for a computer,” said Lance Braunstein, E*Trade CIO, in an interview for the Wall Street Journal.
To that end, the company’s special innovative group has been working on a new conversational AI solution – an intelligent chatbot that could guide younger investors and help more experienced ones monitor their trades.
Indeed, the particular appeal of robo advisors is that they fill in the financial literacy void for millennials and help them start planning their future better. What’s more, as Accenture notes, younger customers are drawn more towards digital solutions rather than in-person conversations with older advisors whenever they seek investment advice.
Robert Golladay, general manager, Europe, at CognitiveScale, shares the same sentiment and says, “The winners in the wealth management space are probably going to use AI to understand how a person wants to be communicated with and marketed to.” Indeed, big data analytics and machine learning enable unprecedented levels of personalization, enabling banks to build a truly 1:1 rapport with each customer, much to their satisfaction.
The future of wealth management will be largely focused on figuring out how to deliver proactive, ultra-personalized, and real-time everyday support to investors of various calibers through digital channels.
In particular, the following AI use cases in wealth management will move from the industry margins to the mainstream:
- Omnichannel, immediate and intuitive offerings via different communication channels – chatbots, mobile app, in-person verbal communication, etc.
- Ultra-personalized advice, tailored to the customers’ current needs and personal circumstances
- A curated selection of financial and investment advice, based on the customers’ known preferences, risk tolerance, and experience-level
- Proactive guidance and advice, enabling the customer to continuously learn and improve their financial knowledge
AI will play a central role in such solutions, as it is the advanced deep learning algorithms that can enable personalization at scale plus supply advisors with a real-time stream of predictive and prescriptive insights.
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